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. 2007 Nov-Dec;14(6):765-71.
doi: 10.1197/jamia.M2134. Epub 2007 Aug 21.

The value of patient self-report for disease surveillance

Florence T Bourgeois  1 , Stephen C Porter, Clarissa Valim, Tiffany Jackson, E Francis Cook, Kenneth D Mandl
Affiliations

The value of patient self-report for disease surveillance

Florence T Bourgeois et al. J Am Med Inform Assoc. 2007 Nov-Dec.

Abstract

Objective: To determine the accuracy of self-reported information from patients and families for use in a disease surveillance system.

Design: Patients and their parents presenting to the emergency department (ED) waiting room of an urban, tertiary care children's hospital were asked to use a Self-Report Tool, which consisted of a questionnaire asking questions related to the subjects' current illness.

Measurements: The sensitivity and specificity of three data sources for assigning patients to disease categories was measured: the ED chief complaint, physician diagnostic coding, and the completed Self-Report Tool. The gold standard metric for comparison was a medical record abstraction.

Results: A total of 936 subjects were enrolled. Compared to ED chief complaints, the Self-Report Tool was more than twice as sensitive in identifying respiratory illnesses (Rate ratio [RR]: 2.10, 95% confidence interval [CI] 1.81-2.44), and dermatological problems (RR: 2.23, 95% CI 1.56-3.17), as well as significantly more sensitive in detecting fever (RR: 1.90, 95% CI 1.67-2.17), gastrointestinal problems (RR: 1.10, 95% CI 1.00-1.20), and injuries (RR: 1.16, 95% CI 1.08-1.24). Sensitivities were also significantly higher when the Self-Report Tool performance was compared to diagnostic codes, with a sensitivity rate ratio of 4.42 (95% CI 3.45-5.68) for fever, 1.70 (95% CI 1.49-1.93) for respiratory problems, 1.15 (95% CI 1.04-1.27) for gastrointestinal problems, 2.02 (95% CI 1.42-2.87) for dermatologic problems, and 1.06 (95% CI 1.01-1.11) for injuries.

Conclusions: Disease category assignment based on patient-reported information was significantly more sensitive in correctly identifying a disease category than data currently used by national and regional disease surveillance systems.

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Figures

Figure 1
Figure 1
Recursive partitioning tree for classification of gastrointestinal problems. GI = gastrointestinal problem, Class = disease category assigned by the tree, Case = actual outcome as measured by gold standard, N = total number of subjects in each node of the tree.
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